ABSTRACT The relation between temperament and happiness in children aged 8-12 was examined. Participants included 311 students in Grades 4-6 and their parents, recruited from public and private schools in the Central Okanagan. Parents rated their children’s temperament using the Emotionality, Activity, and Sociability (EAS) Temperament Survey (Buss & Plomin, 1984) and rated their children’s happiness using a single-item measure. Children rated their own temperament using the EAS Temperament Survey and the PiersHarris Self Concept Scale for Children, Second Edition (Piers-Harris 2) (Piers & Herzberg, 2002). Children also rated their own happiness using a single-item measure, the Oxford Happiness Scale, Short Form (Hills & Arygle, 2002), and the Subjective Happiness Scale (Lyubomirsky & Lepper, 1999). Confirmatory factor analyses established that parent and child ratings on the EAS Temperament Survey conformed to the four-factor structure proposed by Buss and Plomin (1984). Multiple regression analyses revealed that temperament accounted for between 9-29% of the variance in children’s happiness depending on the rater (i.e., parents vs. children) and the measure of happiness. Individual temperament variables that predicted a unique amount of the variance of children’s happiness over and above the combined effect of all temperament variables varied with the rater of children’s temperament (i.e., parents vs. children) and with the measure of happiness. Children who were more social, less shy, less emotional, and more free from anxiety rated themselves, and were rated by others, as happier. Children who scored higher on the activity temperament rated themselves, and were rated by others, as happier. The results of the current study parallel results of research investigating the relation between happiness and personality in adults. It establishes a strong relation between temperament and happiness, and ii

supports the use of self-reports with children. Implications and suggestions for future research are discussed.

Defining Happiness………………………………………………………..…. 3 Measuring Happiness……………………………………………………….....6 Correlates of Happiness…………………………………………………….....9 Happiness and Personality…………………………………………………...13 Temperament………………………………………………………………...15 Defining Temperament……………………………………………………....16 Models of Temperament…………………………………………………......17 Measuring Temperament in Children……………………………………......22 Development of Temperament……………………………………………....24 Temperament and Happiness………………………………………………...25 The Influence of Culture on Happiness and Temperament…………….……25 The Current Study………………………………………………………..…..27

Skewness and Kurtosis of Variables Before and After Transformation…..…39

Table 2.

Means and Standard Deviations of Variables Included in Analyses……..….40

Table 3.

Pearson Product Moment Correlations Between the Four Measures of Happiness: Children’s Self-Ratings of Happiness, Parents’ Ratings of their Children’s Happiness, the Subjective Happiness Scale, and the Oxford Happiness Questionnaire, Short Form……………………………………….48

Pearson Product Moment Correlations Between the Piers Harris Freedom From Anxiety Sub-Domain and Parents’ Ratings of their Children on the EAS Measures: Emotionality, Activity, Sociability, and Shyness………………...50

Figure 1. Participants’ ratings of happiness using the Faces Scale………………………41

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ACKNOWLEDGEMENTS I would especially like to recognize several individuals without whom this thesis would not have been possible. To my advisor, Dr. Mark Holder, I am thankful for all of the guidance, support and understanding he has given me throughout this process. I would like to thank my fellow student and good friend, Judi Wallace, for allowing me to join my survey materials with hers and for partnering with me for data collection. In addition, I am grateful for her friendship, support, and incredible organization throughout this entire journey. To my committee members, Dr. Colin Reid and Dr. Ben Coleman, I am thankful for their input and suggestions and for taking the time to review previous versions of this thesis. I would also like to acknowledge Rob Callaway for reading and commenting on an earlier version of this thesis. Finally, I would like to thank my family for their support. I am especially grateful for my husband, Cody Klassen, whose love and support has allowed me to pursue and achieve my academic goals.

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DEDICATION

For my Omi, Erna Neumann, who taught me the meaning of hard work, inner strength and perseverance. I wish more than anything that you were here for the completion of this chapter in my life.

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1. Introduction Historically, psychological research has focused heavily on negative aspects of emotion (Furnham & Petrides, 2003). However, a paradigm shift was acknowledged when Dr. Martin Seligman was elected president of the American Psychological Association in 1996 and made the study of positive psychology his primary mandate (Authentic Happiness, 2006). Recent years have seen a proliferation of rigorous empirical research, journal articles, books, and programs devoted to positive psychology (Seligman, Steen, Park, & Peterson, 2005). Happiness researchers have begun to extend their target audience from academia to the general public [e.g., Seligman’s (2002) book titled Authentic Happiness and a website of the same name which provides free information on happiness and happiness increasing strategies (Authentic Happiness, 2006)]. In addition, Peterson and Seligman’s (2004) book entitled Character Strengths and Virtues: A Handbook and Classification intended to do for positive psychology what the American Psychological Association’s Diagnostic and Statistical Manual did for psychological disorders (Seligman et al., 2005). That is to say that they created a manual, based on theory and empirical research, to guide readers to find their own strengths and virtues and learn to use them to their advantage. Seligman and his colleagues claim that the study of positive psychology is a valid scientific endeavor and what is right with people deserves as much attention as what is wrong. The current study seeks to investigate the relation between happiness (a facet of positive psychology) and temperament in children. Although several important correlates of happiness in adults have been identified, analogous studies with children are not common (Mahon & Yarcheski, 2002). Nevertheless, a recent survey of adults in 48 countries revealed

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that what adults desire most for their children is a high level of happiness (Diener & Lucas, 2004). In particular, although it was true for adults in all countries, Canadian adults, on average, had the highest desire for their children’s happiness. Thus, because it is such a highly desirable characteristic, it is important for empirical research to investigate children’s happiness. Including children in the study of happiness is important for several reasons. First, the predictors of happiness in children may be different from those in adults. For children, happiness may be found in the domains of personal and home life (Noddings, 2003) and may be closely linked to experiencing pleasurable stimuli (Kornilaki & Chlouverakis, 2004). In addition, several factors that have been identified as important to happiness in adults do not apply to children: marriage (Efkildes, Klaitzidou, & Chankin, 2003), occupation (Argyle, 2001), spousal happiness (Stull, 1998), and having children (Efkildes et al., 2003). Furthermore, predictors of life satisfaction have been shown to change with age (Harry, 1976). For instance, academic test scores predicted life satisfaction in Grade 2, but not in Grade 8 (Chang, McBride-Chang, Stewart, & Au, 2003). It is appropriate to study children because by middle childhood they hold more complex self-views and can describe themselves using trait labels (Shiner & Caspi, 2003). These children are old enough to both identify and use emotions in complex social environments (Schultz, Izard, & Bear, 2004), and they are able to consider multiple sources of information when processing emotions (see Berk, 1994 for a review). In order to illuminate the importance and potential implications of the present study, it is important to first define happiness, explain how it is assessed, review what past research

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has already revealed, and identify why it is important to study happiness in relation to temperament. 1.1 Defining Happiness Researchers have not agreed on a standard definition for happiness; however many important themes have consistently emerged. Happiness has been described in many ways, including as an overall perception of life satisfaction (Huebner, 1991), as affective and cognitive evaluations of one’s life (Demir & Weitekamp, 2006), as the presence of positive affect and the absence of negative affect (Argyle, 2001), and as experiencing pleasure, engagement, and meaning in one’s life (Seligman et al., 2005). Underlying all of these descriptions is the widely accepted belief that happiness is relatively stable over time, reflecting a trait rather than a current state (e.g., Kozma & Stones, 1983; Lu & Argyle, 1991; Stones & Kozma, 1988; Stull, 1988). Although Argyle (2001) suggests happiness is the presence of positive affect and the absence of negative affect, positive and negative affect may not be polar opposites of a single continuum. Rather, they may be two independent dimensions (Lykken & Tellegen, 1998). Some researchers consider happiness as a balance of positive and negative hedonic values (Schimmak, 2003). However, this does not necessarily imply that the more positive affect a person experiences, the less negative affect he or she will experience. Instead, the relative proportions of each type of affect are important to an overall judgment of happiness. Indeed, research has demonstrated positive and negative affect to be separate constructs, which become increasingly separated over time (Diener, Suh, Lucas, & Smith, 1999). That is to say that in moment-by-moment fluctuations in mood, positive and negative affect are more closely related than when they are considered over a long period of time.

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The terms happiness, life satisfaction, and subjective well-being are often used interchangeably (e.g. Pavot, Diener, & Fujita, 1990; Stokes & Frederick-Recascino, 2003; Swinyard, Kau, & Phua, 2001). However, several studies emphasize the differences between these three constructs, arguing that each has separate sets of correlates and predictors (e.g., Efkildes et al., 2003; Harvey, Bond, & Greenwood, 1991; Hayes & Joseph, 2003; McLanahan & Adams, 1989). For example, positive and negative affect, gender, and having children influenced respondents’ happiness, but not life satisfaction or subjective well-being (Efkildes et al., 2003). Although these three constructs are not identical, they cannot be completely disentangled. Several studies illustrate the relatedness and interdependence of happiness, life satisfaction, and subjective well-being (e.g., Argyle, 2001; Diener et al., 1999; Huebner, Suldo, Smith, & McKnight, 2004; Mikulincer & Peer-Golding, 1991; Pinquart & Sorensen, 2001; Schimmak, 2003). From these studies, subjective well-being emerges as the most global concept (Huebner et al., 2004) while life satisfaction emerges as an essential component of subjective well-being (Diener et al., 1999), and happiness emerges as the affective component that underscores both subjective well-being and life satisfaction (Huebner et al., 2004; Schimmak, 2003). For the purposes of this study, happiness will be considered an underlying, affective component to both life satisfaction and subjective wellbeing. Research has shown that major life events may not have equally large and lasting effects on happiness. For example, lottery winners who described their wins as highly positive events did not show significantly different happiness ratings compared to a control group (Brickman, Coates, & Janoff-Bulman, 1978). Furthermore, in the same study, paraplegics who acquired their disabilities as a result of an injury rated their happiness levels

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as above the midpoint. Further research has demonstrated happiness to be stable over time, and this stability led to a set point theory of happiness (Lucas, Clark, Georgellis, & Diener, 2003). The set point theory posits that, in general, people have stable levels of happiness that undergo temporary fluctuations due to both positive life events (e.g., marriage), and negative life events (e.g., death of a spouse). According to the theory, immediately following a major life event, individuals’ happiness levels may rise or fall; however, many will eventually return close to their previous levels. These findings have led researchers to question whether the set point theory precludes happiness levels from permanent attempts at improvement or change. Recent research reveals that long-term levels of subjective well-being can in fact undergo permanent change and that adaptation to new situations is not inevitable (Lucas, 2007). Some examples of adaptation from this study include findings that people generally adapt to marriage within two years, and after the death of a spouse, happiness levels return almost to their previous levels after seven years. However, the study also found evidence for permanent change in that divorce, unemployment, and serious disability can cause significant decreases in happiness levels, which never fully rebound. Furthermore, there are individual differences in the degree of adaptation people experience (Diener, Lucas, & Scollon, 2006). Closely related to stability (and perhaps its underlying process) is a genetic, heritable component to happiness. Twin studies revealed that over a span of 10 years, monozygotic twins’ ratings of happiness correlated highly (r = .40) while dizygotic twins’ ratings do not (r = .07) (Lykken & Tellegen, 1996). The authors claim that genetic variables determine approximately 80% of the stability in happiness ratings but that overall, adult happiness is equally influenced by genetic and environmental, and experiential factors. Recent research revealed that the stable component of happiness accounted for approximately 34%-38% of

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the variance in happiness (Lucas & Donnellan, 2007). Taking these results together, approximately 38% of happiness is accounted for by a stable factor, and approximately 80% of that stable factor is determined by genetics. Therefore, while happiness is stable to a certain extent, individuals’ overall happiness levels are subject to external influences and individual differences, and are not immune to change (Lucas, 2007). This is encouraging for those who seek to improve their happiness levels. Indeed, early research in this area has shown that happiness enhancing strategies can effect long-term improvements in happiness levels (Seligman et al., 2005). For the purposes of this study, happiness is defined as a relatively stable, partially heritable positive affective trait, which consists of an overall positive subjective evaluation and underscores both life satisfaction and subjective well-being. 1.2 Measuring Happiness Just as previous studies have used various definitions of happiness, so too have they used various measures to assess happiness. Self-report questionnaires and reports by knowledgeable others (e.g., parents, friends, and spouses) are common methods of evaluating happiness (Pavot & Diener, 1993). Self-ratings are important and valid because happiness research is interested in how people perceive themselves (Myers & Diener, 1995). Furthermore, multiple ratings of a person’s happiness tend to show convergent validity (Myers & Diener). For example, the happier people rate themselves to be, the happier they are rated by friends and family. Reports by knowledgeable others are reliable and valid and show greater stability when positive affect is being rated (Lepper, 1998). Furthermore, using self- and other-reports in concert helps to control for response factors such as transient mood states or social desirability biases (Lepper, 1998). Although measures of social desirability

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have been found to correlate with both self- and other-reports of happiness, it is suggested that social desirability is an element of personality related to well-being rather than a source of error (Diener, Sandvik, Pavot, & Gallagher, 1991) Single-item measures are commonly used to assess happiness and are an example of self- or other-reports. These measures are usually embedded within a questionnaire asking a variety of questions, and consist of a single question designed to assess the overall happiness of the respondent. Studies utilizing one-item measures have found them to be both reliable and valid (Harry, 1976; Stull, 1988; Swinyard et al., 2001). An example of a single-item measure is the Faces Scale. First used by Andrew and Withey (1976), the Faces Scale has been adapted for use with children aged 8-12 years old (Holder & Coleman, 2008, in press). The scale consists of seven drawings of faces ranging from very unhappy to very happy and targets a global assessment of happiness by asking respondents to choose the face that represents how they feel most of the time. The Faces Scale is especially suitable for use with children because children as young as 3 years of age can recognize and label emotions, they perform best when emotions are represented as schematic drawings as opposed to photographs, and they are best at labeling happiness, followed by sadness (MacDonald & Kirkpatrick, 1996). Multiple-item measures of happiness are also commonly employed in research. These measures include multiple item questionnaires such as the Oxford Happiness Questionnaire, Short Form (Hills & Argyle, 2002), and the Subjective Happiness Scale (Lyubomirsky & Lepper, 1999). Individuals are asked to read each item and respond according to a particular scale, often a Likert-type scale (e.g., 1 = strongly disagree, 7 = strongly agree). Multiple-item measures are also examples of self- or other-reports.

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Happiness has also been assessed using visual analogue scales. Visual analogue scales can be compared to thermometers. The respondent has an anchor on each end of the scale (e.g. “very unhappy” and “very happy”) and may choose a point anywhere on the line that best represents their response. Although suitable for use with adults, research has demonstrated that children have difficulty using visual analogue scales, especially children 8 years of age and younger (Shields, Cohen, Harbeck-Weber, Powers, & Smith, 2003). Children 10 years of age also experienced difficulty and a lack of understanding, even after receiving training with the scale. Thus, although these scales may be appropriate for adults, they are less suitable for children. Experiential research has also been employed to explore happiness (e.g., Csikszentmihalyi & Hunter, 2003; Schimmack, 2003). In this type of research, participants are given pagers to wear at all times. They are paged at random times throughout the day and must record what they are doing and how they are feeling at that moment. This technique has been used with children as young as Grade 6 (approximately 12 years old) (Csikszentmihalyi & Hunter, 2003). Experiential research measures fluctuations in mood throughout the day, which differs from the goal of the present study, which is to measure global happiness. Although there are several ways to effectively measure happiness, there is no clearly accepted method, and most researchers agree that using multiple measures of happiness is optimal (DeNeve & Cooper, 1998). In fact, a meta-analysis showed that 91% of studies comparing subjective well-being to variables of interest used multiple subjective well-being measures. Through employing the methods of measurement described above, research has revealed several important predictors of happiness.

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1.3 Correlates of Happiness Although a complete review of happiness-related research is beyond the scope of this study, it is important to review some of the more commonly studied predictors of happiness as well as the limited number of studies that have been conducted with children. The following list is by no means exhaustive. Happiness studies with adolescents, adults and the elderly have yielded some general and consistent findings. Overall, people rate themselves as happy (Lykken & Tellegen, 1996). Many studies reveal that happiness measures are often positively skewed (Peterson, Ruch, Beermann, Park, & Seligman, 2007). In fact, the mean subjective well-being ratings of adults are well above neutral (Lykken, 2007). Although no single variable can guarantee happiness (Diener & Seligman, 2002), many variables have been examined in relation to happiness in an attempt to discover which factors contribute to individuals’ overall happiness. In general, demographic variables tend to show weak, but significant correlations with happiness in adults, although they do not account for large proportions of the variance in happiness (Amato, 1994). In particular, age, gender, education, and employment are not strong predictors of happiness. Gender does not significantly correlate with happiness, although the predictors of happiness may differ for men and women (Hills & Argyle 2001b; Lu & Lin, 1998). Age is also a weak predictor of happiness (Pinquart & Sorensen, 2001). For example, in one study, gender and age accounted for 2% of the variance of happiness (Cheng & Furnham, 2003). Income tends to be weakly positively correlated with happiness (Ellison, 1991), especially in affluent countries (Argyle, 2001). However, for those who are poor, income is more strongly positively correlated with happiness (Amato & Zuo, 1992). Having

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enough wealth to cover the basic necessities in life is necessary but not sufficient for happiness (DeNeve & Cooper, 1998). Research with children parallels research with adults regarding demographic variables. In a study of the correlates of life satisfaction in children in Grades 5-7, demographic variables failed to show a significant relation with life satisfaction (Huebner, 1991). Furthermore, family demographic variables such as the number of siblings and the age of parents are not strongly correlated with children’s happiness (Holder & Coleman, 2008, in press). However, there are particular aspects of family life that are related to children’s happiness. One researcher suggests that for children, happiness lies in the domains of personal and family life (Noddings, 2003). Family stability in early childhood is important for later adjustment of children, especially for those who come from economically disadvantaged families (Ackerman, Kogos, Youngstrom, Schoff, & Izard, 1999). In a study of middle-school children, children’s perceptions of the quality of their family relationships had the strongest correlation with their life satisfaction (Ackerman et al., 1999). In addition, retrospective studies demonstrate the closeness of a child to his or her parents predicts that child’s happiness (Amato, 1994). Furthermore, in studying situational differences in relation to happiness, being with a parent, sibling, or other relative was related to average or above average ratings of happiness for children in Grades 6-12 (Csikszentmihalyi & Hunter, 2003). Marriage is consistently associated with higher levels of happiness in adults. One explanation for this is that married people have a permanent social partner. Indeed, the social roles one occupies in marriage may be related to happiness (Wood, 1989). Research with African American, dual-career couples demonstrated that the best predictor of a person’s overall happiness was his or her happiness in marriage (Thomas, 1990). Furthermore, in

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married couples, the best predictor of one partner’s happiness is the spouse’s happiness (Stull, 1988). However, the correlation between happiness and marriage may be the result of self-selection because happier people are more likely to get married and stay married than unhappy people (Lucas et al., 2003). Indeed, individuals who eventually marry have higher happiness levels 5 years prior to getting married, while those who get married and eventually divorce have lower happiness levels prior to entering into marriage (Lucas, 2007). Marriage is clearly not an appropriate variable to evaluate in children. However, research has shown that the marital status of one’s parents is not significantly related to children’s happiness (Holder & Coleman, in press). Religiousness is another variable that has been examined in relation to happiness. In general, attendance at religious services is positively correlated with adults’ happiness (Cohen, 2002; Ferriss, 2002; Francis, Jones & Wilcox, 2000). The strength of one’s religious faith also shows a positive correlation with happiness, especially for those who are older and those with a lower IQ (Ellison, 1991). Interestingly, the belief in an immortal life was not found to correlate with a person’s happiness (Ferriss, 2002). Rather, it is more likely that social factors such as a feeling of belonging and congregational support are important contributing factors to the correlation between religion and happiness (Cohen, 2002; Francis et al., 2000). Research has suggested that spirituality is an important predictor of children’s happiness (Wallace, manuscript in preparation). Specifically, believing one’s life has meaning and purpose, and depth of inter-personal relationships between oneself and others were important to children’s happiness.

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Work, or occupation, has also been assessed in relation to happiness. Research demonstrates that the more satisfied a person is with his or her job, the happier that person will be (Argyle, 2001). The most important contributor to job satisfaction may be the social interactions a person experiences at work (Argyle, 1989 as cited in Argyle, 2001). As with marriage, occupation is a variable that is not applicable to the study of happiness in children. Leisure and social activities are strongly related to happiness in adults. Leisure activities are positively related to happiness, especially when these activities involve participation in sports teams (Hills & Argyle, 1998). This correlation is consistent with the finding that physical exercise improves affect (e.g., Carlson, 1982; Dubbart, 2002). It is not necessarily the number of activities a person participates in, but the intensity and commitment a person demonstrates that are important to happiness (Ray & Heppe, 1986). In addition, television viewing is negatively correlated with happiness (Hills & Argyle, 1998). It is suggested that people who watch extensive amounts of television may not have alternative options; for example, they may not have many friends with whom they spend time. Interestingly, those people who regularly watch soap operas do not show these negative effects of television viewing (Hills & Argyle). It is suggested that people watch soap operas for relaxation and entertainment value, rather than because they have no alternative options (Hills & Argyle). Although research has established a clear link between leisure and happiness in adults, and to a lesser extent with adolescents and older adults, further research is needed to investigate the relation to children’s happiness. One study suggests that leisure contributes to children’s happiness (Holder, Coleman, & Zehn, submitted). Specifically, active leisure (e.g.,

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related to athletics) accounted for a significant proportion of the variance in children’s wellbeing while passive leisure activities were weakly negatively correlated with well-being. Social factors have been identified being strongly related to happiness (Argyle, 2001). In an examination of the happiest group of students from a college sample, this group displayed highly social behaviour and demonstrated strong social relationships (Diener & Seligman, 2002). The quality of one’s friendships has also been shown to play a significant role in happiness (Demir & Weitekamp, 2006). Social factors likely contribute to the positive correlations between happiness and various factors discussed here, such as participation in sports teams, work, and attendance at religious services. In addition, social factors may also explain why those who watch soap operas do not experience the same negative impact as other television viewers. There seems to be a parasocial element involved in watching soap operas, in that regular watchers become emotionally involved with the characters (Hills & Argyle, 1998). Social factors are also important to children’s happiness. For instance, items comprising factors such as negative peer relations, interacting with friends and family, and behaving badly toward others accounted for a significant proportion of the variance in children’s happiness (e.g., between 3-32%, depending on the category and which of three happiness measures were employed) (Holder & Coleman, in press). 1.4 Happiness and Personality Throughout the literature, happiness has been consistently and strongly linked to personality. Two particularly important personality traits in this relation are extraversion and neuroticism. Extraversion is characterized by individuals who are social, assertive, lively, and sensation seeking (Eysenk, 1986), as well as expressive, energetic, and dominant (Shiner

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& Caspi, 2003). Neuroticism is characterized by individuals who are anxious, depressed, emotional, and have low self-esteem (Eysenk, 1986) and who are fearful, angry, and insecure (Shiner & Caspi, 2003). Several studies have demonstrated a positive correlation between happiness and extraversion, and a negative correlation between happiness and neuroticism (e.g., Costa & McCrae, 1980; Diener & Seligman, 2002; Furnham & Brewin, 1990; Furnham & Cheng, 2000b; Hills & Argyle, 2001b; Pavot, Diener, & Fujita, 1990). Meta-analytic findings revealed that extraversion was positively related to well-being variables and was the best predictor of happiness (DeNeve & Cooper, 1998). Conversely, neuroticism was the strongest (negative) predictor of well-being. Furthermore, in one study, extraversion and neuroticism accounted for 42% of the variance in adults’ happiness (Brebner, Donaldson, Kirby, & Ward, 1995). Finally, in an investigation of what people believed to be the most important predictors of happiness, participants identified both extraversion and neuroticism as important factors (Furnham & Cheng, 2000a). Extraversion and neuroticism are characterized as “superfactors,” or higher-order personality traits that encompass a host of more specific, lower-order traits (Shiner & Caspi, 2003). Examples of lower-order traits that are also associated with adults’ happiness include assertiveness (Argyle & Lu, 1990), sociability (Weinstein & Mermelstein, 2007), emotional stability, locus of control, positive affectivity (DeNeve & Cooper, 1998), attributional style, optimism, and self-esteem (Cheng & Furnham, 2003). McCrae and Costa (1991) proposed two mechanisms through which extraversion and neuroticism exert their influence on happiness. They labeled the first the “temperamental path”, where they propose that being extraverted predisposes individuals to experience positive affect, while being neurotic predisposes individuals to experience negative affect,

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and these experiences impact levels of happiness. The second mechanism is labeled the “instrumental path” and posits that extraversion and neuroticism predispose individuals to experience certain situations that are respectively conducive to high or low levels of happiness. For example, extraverts may seek out social situations that serve to increase their happiness levels. Research has found support for both of these proposed pathways (Shiner & Caspi, 2003; Tkach & Lyubomirsky, 2006) but neither has emerged as the definitive method through which personality influences happiness. Although extraversion and neuroticism show the strongest relation, several other personality variables (including some of the “lower-order” traits mentioned above) have been linked to happiness. For example, assertiveness was positively correlated with happiness, predicted happiness in a longitudinal regression analysis, and could possibly mediate the effect of extraversion and neuroticism on happiness (Argyle & Lu, 1990). Furthermore, attributional style accounted for 18% of the variance of happiness in one study (Cheng & Furnham, 2003). Those who attributed positive outcomes to themselves and who believed that those positive outcomes would occur again and have positive effects on their lives, had higher happiness scores. Furthermore, self-esteem and attributional style combined accounted for 55% of the variance in happiness. Finally, a meta-analysis (DeNeve & Cooper, 1998) investigating the correlates of subjective well-being showed a number of variables to be correlated with happiness: emotional stability (r = .36); locus of control-chance (r = -.34); hardiness (r = .32); and positive affectivity (r = .31). 1.5 Temperament As personality has been so strongly and consistently linked to happiness and wellbeing in adults, an analogous relation might exist in children. However, research shows that

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an individual’s personality may not become stable until age 30 (Costa & McCrae, 1994) or even 50 (Shiner & Caspi, 2003). Thus, throughout infancy, childhood, and even adolescence, when personality is thought to be in its developing stages, personality constructs are referred to as temperament. Temperament is generally accepted by personality theorists to be the foundation of adult personality (Buss & Plomin, 1984). The distinction between temperament and personality becomes increasingly ambiguous after infancy and little is known about the development of temperament into personality (Shiner & Caspi, 2003). However, temperament is believed to comprise the whole of personality in infancy, while forming a subset of personality traits as individuals develop and mature through later childhood (Shiner & Caspi). In order to better understand how temperament might be studied in relation to happiness, it is important to explore its definitions and origins, popular models of temperament and how it is measured, the developmental process from temperament to personality, and important theoretical links between temperament and happiness. 1.6 Defining Temperament As with many psychological constructs there is no single, standardized definition of temperament. However, key concepts are shared by many of the different definitions. At the core of defining temperament is the measurement of observable emotion, with a particular focus on negative emotionality (Belsky, Hsieh, & Crnic, 1996). This focus is a result of the link between negative emotionality and later problematic behaviour, and also that negative emotionality is usually very visible, easy to measure, and parents are more responsive to it (Belsky, Fish, & Isabella, 1991). In addition to the measurement of emotion, definitions of temperament often highlight the measurement of other overt behaviours, such as general activity level (e.g., motor activity) and overall reactivity (e.g., reaction to new

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stimuli/situations) (Karrass & Braungart-Rieker, 2004; Rothbart, Ahadi, & Evans, 2000). In order to be classified as a temperament, a trait must be observable in early life (i.e., ideally within the first 2 years) (Buss & Plomin, 1984). Furthermore, temperament traits show a degree of temporal and situational stability (Shiner & Marmorstein, 1998). Research shows that temperament is relatively stable between the ages of 3 and 7 and especially by the ages 8 to 12 (Buss & Plomin, 1984). Theorists agree, however, that despite its stability, temperament follows a developmental process (Shiner & Marmorstein, 1998), and is influenced throughout this process by children’s inevitable maturation and life experience (Else-Quest, Hyde, Goldsmith, & VanHulle, 2006). Finally, definitions of temperament often also require temperament traits to be constitutional in nature (i.e., have a biological basis and are heritable) (e.g., Buss & Plomin, 1984; Rothbart et al., 2000). 1.7 Models of Temperament As part of the New York Longitudinal Study (NYLS) in 1963, Thomas and Chess launched the first large-scale study of infant temperament, which is now considered a standard in the field (Vaughn, Taraldson, Chuchton, & Egeland, 2002). Participants were the parents of 2-6 month old infants from 84 families (Buss & Plomin, 1984) with whom Thomas and Chess conducted a lengthy and in-depth clinical interview (Rothbart et al., 2000). From these interviews the researchers used factor analysis to reveal nine key dimensions of temperament: activity level; approach-withdrawal; rhythmicity; adaptability; general mood; intensity; attention span and persistence; distractibility; and threshold of response to stimulation (Lemery, Goldsmith, Klinnert, & Mrazek, 1999). Based on infants’ scores on these nine dimensions, they were classified as having one of three temperaments: easy, difficult, or slow-to-warm-up (Belsky et al., 1991). Of primary interest is the difficult

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temperament because it has been linked with negative outcomes. Thomas and Chess defined a difficult infant as one who would withdraw from new experiences, adapt slowly to new situations, have irregular biological rhythms (i.e., eating and sleeping), display intense emotional reactions, and have an overall negative mood (Belsky et al., 1991). This research sparked the development of questionnaires such as the Infant Temperament Questionnaire (Carey, 1973), and the Infant Behaviour Questionnaire (Rothbart, 1981) that could be used in place of the lengthy clinical interview to further explore the nine temperament traits (Vaughn et al., 2002). Although important, this influential research was not without its problems. As temperament research proliferated, attempts to replicate Thomas and Chess’ nine dimensions of temperament failed (Buss & Plomin, 1984). Further attempts produced merely four dimensions (Shiner 1998). Furthermore, although the face validity of the easy, difficult, and slow-to-warm-up classifications was good (Buss & Plomin, 1984), a difficult temperament did not necessarily mean the same thing to all parents and researchers (Goldsmith et al., 1987). Finally, Thomas and Chess’ primary goal was to be able to predict later developmental problems and psychopathology (Shiner & Marmorstein, 1998), and while useful, their research focused solely on infants and speculated about but did not discuss the origins of temperament (Buss & Plomin, 1984). Research has led to the development of many theories regarding the structure and dimensions of temperament; however, there is no single all-encompassing theory that measures the full range of traits (Shiner & Marmorstein, 1998). The following explores some of the more prominent models of temperament in an effort to establish which model is best suited to the current study.

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Cloninger, Svrakic, and Przybeck (1993) developed a psychobiological model of temperament and character designed to help predict disorders and distinguish between personality disorder subtypes. Though largely used with adults, researchers claim the model can be applied to children. Their model includes four temperaments: novelty seeking (a behavioural activation system), harm avoidance (a behavioural inhibition system), reward dependence (a system which functions to maintain behaviours) and persistence. The research conducted by Cloninger and colleagues revealed that their proposed temperaments do not explain behaviours such as social cooperation, agreeability, compassion, and acceptance (i.e., more positive behaviours). Thus, they added three character dimensions to their model: selfdirectedness, cooperativeness, and self-transcendence. Their research showed that these higher order character traits tended to increase with age (the youngest participant was 18 years old). Thus, because of its focus on older individuals and predicting pathology, and the inability of the temperament dimensions to predict many positive behaviours, the model proposed by Cloninger and his colleagues is not appropriate for the current study. Rothbart (1981) created a psycho-biological model of temperament which focused on individual differences in reactivity and self-regulation. Reactivity was defined as responses to stimulation across emotional, attentional, and motor domains, while self-regulation was defined as an approach or avoidance strategy that modulated reactivity (Rothbart, 1988). In order to measure temperament in 4-7 year old children, Rothbart (1986) created a questionnaire comprised of questions from 15 scales, which were analyzed to reveal three higher-order factors: positive emotionality, or extraversion, negative emotionality, or neuroticism, and constraint, or inhibitory control. A major advantage of Rothbart’s model was that unlike other models, she incorporated aspects of positive affect (Shiner &

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Marmorstein, 1998). Disadvantages include the fact that this model focuses on younger children than the age group of interest for the current study and, more importantly, the framework of her temperament model was not formed through theory (Goldsmith et al., 1987). Recent years have seen a growth in popularity in applying the five-factor model of personality (commonly used to study adult personality) to samples of adolescents and children (Shiner & Marmorstein, 1998). The five factor model, developed by Costa and McCrae (1990), consists of five broad personality traits: Extraversion, Neuroticism, Agreeableness, Conscientiousness, and Openness to Experience. Recent meta-analytic research supports the comprehensiveness of the five-factor model and claims that dimensions from other inventories fall under the broad umbrella of the five factors (O’Conner, 2002). Some researchers advocate the use of adult personality measures with adolescents (e.g., McCrae, Costa, & Terracciano, 2002). Recent research with a sample of Dutch youths revealed a clear-cut factor structure and sufficient validity; however, the Openness to Experience factor was problematic (as has also been demonstrated in research with adults) (Muris, Meesters, & Diederen, 2005). A review of the research using children and adolescents reveals that although there are similarities to studies with adults, some of the subitems of specific factors are different for children, additional factors such as activity and irritability appear for children, and teachers’ responses give a closer match to the five factors than either parent or self-reports (Shiner & Marmorstein, 1998). Due to these discrepancies as well as the fact that, once again, the big five factors do not have their foundation in psychological theory (they were created by factor-analyzing adjective lists) (Shiner & Marmorstein, 1998), this model will not be used for the current study.

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The Emotionality, Activity, and Sociability (EAS) theory of temperament developed by Buss and Plomin (1984) is a theoretically based model that requires temperament traits to be heritable, observable in early life, and show a degree of stability and continuity with age. Buss and Plomin chose to focus on broad traits in order to capture behaviours that occur in most situations and on traits that are most meaningful or important to an individual (e.g., traits that are relatively stable and can still be seen in later life). Just as personality constructs are organized hierarchically, so too are temperament traits (Shiner & Caspi, 2003). Thus, since this study reflects an early attempt to comprehensively investigate the relation between happiness and temperament in children, it is important to focus on broader, higher-order traits in order to determine which lower-order traits may warrant further investigation. The EAS theory (Buss & Plomin, 1984) includes three temperament traits. Emotionality (primarily negative) is described as distress, or the tendency to become upset easily and intensely. It is manifested as general distress in infants and differentiates into fear and anger in later childhood. Sociability is the tendency to prefer the presence of others to being alone. Activity is comprised of what the researchers label as tempo and vigor, and can be conceptualized in terms of the frequency of activities, the time spent on activities, the intensity of activities (e.g., jumping and bouncing), and choosing high energy activities over low energy activities. In addition to these three temperaments, Buss and Plomin include the dimension of Shyness, characterized as feelings of tension and distress and the tendency to escape from social situations. They emphasize that shyness is closely related to both sociability and emotionality and is not a temperament in its own right. Buss and Plomin’s (1984) model has received praise for its carefully chosen dimensions which are supported both by theory and psychometric evidence, and for its links

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to research conducted with adults (Shiner & Marmorstein, 1998). Indeed, Buss and Plomin (1984) suggest that high degrees of sociability and low degrees of shyness are akin to the adult dimension of extraversion whereas high degrees of emotionality are akin to the adult dimension of neuroticism. In its development, the EAS model was applied to children aged 1-9 years (Buss & Plomin, 1984) but lends itself easily to a wide age span (Masi et al., 2003). Moreover, the temperaments it describes are observable at all ages (infancy through adolescence) in both clinical and community samples (Masi et al.). In addition, the dimensions of the EAS theory are not subject to the effects of gender, age, or nationality (this is likely due in part to the theory’s emphasis on genetic inheritance)(Boer & Westenberg, 1994). For all of the reasons described, the EAS theory was employed in the current study to investigate the relation between temperament and happiness in children. 1.8 Measuring Temperament in Children When focusing on infant temperament, researchers typically employ questionnaires and/or behavioural observation. Behavioural observation generally occurs either in the home or in a laboratory and can take the form of a standardized battery of activities or general observation that seeks to encompass particular activities and behaviours (Karp, Servin, Stack, & Schwartzman, 2004). The infant’s behaviour is observed and coded by an independent observer so the potential problem of parental bias is avoided (Pauli-Pott, Mertesacker, Bade, Haverkick, & Beckmann, 2003). However, as children age and develop the capacity for language, the need for behavioural observation is diminished because children can answer direct questions. In fact, questionnaires are the most popular method of measurement in both temperament and personality research (Shiner & Caspi, 2003). Using this convenient method of measurement requires acknowledging some important advantages and disadvantages.

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Questionnaires are desirable because they are both cost effective and easy to administer (Karp et al., 2004). Furthermore, they can be standardized and there are norms against which researchers can evaluate new data (Vaughn et al., 2002). Questionnaires can be used to gather information from several sources (e.g., parents, teachers, and children) and researchers are encouraged to use more than one source when investigating temperament (Shiner & Caspi, 2003). Although there is no standard age for the implementation of selfreport questionnaires, they are commonly employed with school-aged children and researchers tend to agree that self-reports are appropriate to use by later childhood (Shiner & Caspi). In addition to self-reports, questionnaires completed by parents are prevalent in the literature. These types of reports are appropriate because reports by knowledgeable others are reliable and serve to ensure self-reports are not influenced by transient factors such as mood and social desirability (Funder, 1991). Furthermore, although parents are not privy to the exact internal states of their children, they have had the opportunity to observe their children’s behaviour across time and situations, and are the most reliable reporters of their children’s functioning (Karp et al., 2004; Vaughn et al., 2002). Despite their many strengths, questionnaires also have significant drawbacks. Foremost, related to the issue of defining temperament, many different questionnaires contain similarly named scales, but these scales actually differ in conceptual meaning and construction (Shiner & Caspi, 2003). As an example, one study found similarly named scales to correlate only modestly while some scales with dissimilar content actually intercorrelated highly (Goldsmith, Rieser-Danner, & Briggs, 1991). The authors note that these problems are generally seen on questionnaires that are not statistically derived. In addition, some researchers claim that parents are biased when rating their children (Seifer, Sameroff, &

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Dickstein, 2004). The root of this argument stems mainly from infant temperament research where parents’ ratings are compared to those of independent observers and when the two are compared, concordance rates are modest at best (Karp et al., 2004; Leerkes & Crockenberg, 2003). However, these potential biases are of greater concern in infancy (Seifer et al., 2004) and these biases can be circumvented or at least reduced by using more than one information source and by measuring more than one temperament trait. 1.9 Development of Temperament Of great interest to the study of temperament is the process through which temperament develops into personality. Understanding this process is limited because there are few extensive longitudinal studies (Shiner & Marmorstein, 1998). However, there are many likely avenues through which temperament becomes personality. For example, Buss and Plomin (1984) maintain that temperament can influence children’s environments. That is to say, children will seek rewards and what makes them comfortable including actively engaging in or avoiding particular situations, and this will shape their personality as they age. In addition, maturation has a significant effect on temperament. In middle childhood, children’s thoughts become more flexible and they are better able to integrate thoughts and ideas (Sameroff & Haith, 1996). In addition, at this stage of development children begin to describe themselves in terms of traits (Harter, 1996). Furthermore, children’s emerging ability to regulate and control both their emotions and behaviour changes how others observe them and, in turn, describe their temperament (Shiner & Caspi, 2003). It is also important to consider that temperament models are often created for the purpose of addressing a specific research question. For example, Thomas and Chess’ research sought to predict difficulties in later life (Shiner & Marmorstein, 1998). Similarly,

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Cloninger and colleagues (1993) wanted to create a temperament model that would differentiate between personality disorders. Temperament models have also been used to investigate different profiles between children with and without ADHD (McIntosh & ColeLove, 1996) and to predict academic achievement (Martin, Drew, Gaddis, & Moseby, 1988). In contrast, Buss and Plomin’s (1984) EAS model of temperament was not created with a specific research question in mind. It was created with careful attention to theoretical and psychometric concerns, and as such, makes it the most appropriate model to use when investigating the relation between temperament and happiness. 1.10 Temperament and Happiness Exploring the relation between happiness and temperament in children is important, and earlier research has suggested such a relation exists. For example, Huebner (1991) found that temperament made a significant contribution to children’s ratings of life satisfaction. In addition, Holder and Coleman (2008, in press) showed that traits akin to neuroticism and extraversion were important contributors to children’s happiness. Despite these links, we cannot assume that studies with children will mirror results found with adults. As previously mentioned, as children develop and mature, the behavioural manifestations of certain traits may change (Else-Quest et al., 2006). Furthermore, some traits (such as activity) are more salient in children (Shiner & Marmorstein, 1998) and, therefore, may prove to be important to children’s happiness. 1.11 The Influence of Culture on Happiness and Temperament Research has shown that there are cultural differences in happiness and well-being (Suh, 2007). In one study, Swiss participants reported higher life satisfaction than Americans (Peterson et al., 2007). In addition, on an international survey of 49 nations, East Asian

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Nations scored lower than Western and European nations; in fact, despite having one of the strongest economies in the world, Japan ranked 42nd among the 49 nations (Voigt, 2004, as cited in Suh, 2007). Suh suggested that the differences in happiness levels between East Asian and Western/European nations can be largely explained through cultural values. He posits that East Asians cultures value the self in the context of a group rather than as an individual. East Asians’ need to belong manifests itself in a heightened sensitivity to social comparisons and social cues. Suh argues that this increased social sensitivity may decrease one’s subjective well-being (e.g., because of excessive worry and constant striving for belonging and acceptance). Research supports differences in cultural values related to happiness. For example, Americans tend to believe that very happy people possess more positive than negative traits, while the Japanese associate very happy people with more negative traits such as being shallow and egocentric (Suh & Diener, 2006, as cited in Suh, 2007). Furthermore, in Western cultures being unhappy is viewed as unusual and also as the unhappy individual’s fault, whereas extremely positive emotions are less valued in East Asian cultures (Suh, 2007). Differences in cultural values are evident; therefore, researchers suggest that life satisfaction in a given nation is related to living in accordance with the strengths that are valued in that particular nation (Peterson et al., 2007). The relation between temperament and happiness may also be affected by culture. Research with college students from 41 nations revealed that only 6 nations showed a correlation between extraversion and life satisfaction that was above r = .30 (Vitterso, 1998, as cited in Singh, 2008), which suggests that the influence of personality variables on life satisfaction varies by culture. A study of university students in India revealed that

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extraversion, conscientiousness, and openness to experience were all positively correlated with life satisfaction, meaning in life, positive affect and gratitude, and that personality variables accounted for 9% of the variance in life satisfaction (Singh, 2008). In contrast, studies conducted in North America have shown personality variables to account for as much as 55% of the variance of happiness in adults (Demir & Weitekamp, 2006). Thus, the strength of the relation between personality variables and happiness may vary between cultures. By extension, it is likely that temperament variables may differentially influence happiness in children depending on culture. Cross-cultural studies investigating personality and temperament have been pursued with adults, but not with children (Shiner & Caspi, 2003) 1.12 The Current Study The present study seeks to further investigate the relation between temperament and happiness. If this relation is analogous to the relation between personality constructs and happiness in adults, then there are two expected findings. First, children scoring higher on items measuring traits akin to extraversion will rate themselves and will be rated by others as happier than children scoring lower on these items. Second, children scoring higher on items measuring traits akin to neuroticism will rate themselves and will be rated by others as less happy than children scoring lower on these items. Research often relies on parent-reports to evaluate temperament; however, the current study seeks to evaluate whether children’s self-reports of temperament can be validly used as a research tool. Answering these questions and determining the traits important to happiness in children will help inform programs aimed at promoting

well-being in children. For

example, recent research with adults revealed that individuals’ personalities influenced the

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types of happiness-increasing strategies they chose to employ (e.g., extraverts chose more effective strategies than those who were high on neuroticism) (Tkach & Lyubomirsky, 2006). Thus, if a similar relation exists in children, the current study could inform researchers and program developers as to which children, depending on their temperament, might be most receptive to particular strategies.

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2. Methods This study was completed as a part of a larger study investigating the correlates of happiness in children. Data was collected in conjunction with another graduate student, Judi Wallace, whose thesis focused on the relation between happiness and spirituality in children. 2.1 Participants Students, their parents, and teachers were recruited voluntarily from both public and independent schools in the Kelowna area during the 2006-2007 academic school year. Seven hundred and sixty-one Grade 4, 5, and 6 students from 22 classrooms in 4 public schools within School District #23, and from 7 classrooms in 2 independent schools were given packages containing information letters, consent forms, and questionnaires to be brought to their parents/guardians/caregivers (see Appendix A). Over 99% of the adults were the children’s parents; therefore, they are referred to as “parents” for the remainder of this thesis. In total, 476 (63%) of these packages were returned. Of these, 359 (75%) parents consented to their children’s participation, 84 (18%) declined, and 33 (7%) questionnaires were returned completed, but with no consent form and no identifying information. Of the 359 positive consents, 320 (89%) students assented on test day, 13 (4%) declined, and 26 (7%) students were absent. This resulted in a sample of 320 students (51% girls, 49% boys) with an average age of 10 years (M = 10.26, SD = .96), and their parents. Twenty-nine classroom teachers also participated in the study. 2.2 Materials To evaluate the relation between temperament and happiness in children, five questionnaires were used: the Piers-Harris Children’s Self-Concept Scale, Second Edition (Piers-Harris 2; Piers & Herzberg, 2002), the Faces Scale, the Subjective Happiness Scale

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(Lyubomirsky & Lepper, 1999), the Oxford Happiness Questionnaire (Hills & Arygle, 2002), and the Emotionality Activity and Sociability (EAS) Temperament Survey (Buss & Plomin, 1984). Teachers were asked to rate the happiness of participating children in their classrooms using the Faces Scale. Parents were asked to rate their children’s temperament and happiness by completing the EAS Temperament Survey as well as the Faces Scale, while children were asked to complete all five measures. When an item required a response within a range (e.g., 1 through 7), Likert-type scales were used. Research shows that children understand Likerttype scales better than visual analogue scales (even with explicit instruction designed to increase children’s understanding) (Shields, Cohen, Harbeck-Weber, Powers, & Smith, 2003), and also prefer filling in circles and having more, as opposed to fewer, response options (Rebok et al., 2001), as are provided through Likert-type questions. 2.2.1 Piers-Harris Children’s Self-Concept Scale, Second Edition (Piers-Harris 2) (Piers & Herzberg, 2002). The Piers-Harris 2 is a standardized, 60-item, self-report questionnaire designed for use with children aged 7-18 years. It assesses 6 specific subdomains of self-concept: Behavioural Adjustment, Intellectual and School Status, Physical Appearance, Freedom from Anxiety, Popularity, and Happiness and Satisfaction. Students were asked to respond to the 60-items by filling in “yes” or “no” for each statement. The statements express how students may feel about themselves (e.g., “I am a happy person”; “I like being the way I am”). The Piers-Harris 2 is a reliable and valid measure (Marsh & Holmes, 1990; Piers & Herzberg, 2002) that has been used to examine relationships between self-concept and other trait-like behaviours (e.g., personality), and is easily administered to groups (Piers & Herzberg). Reliability analyses indicate that the present sample was within the “Average” range according to test norms (see Appendix C).

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The Freedom from Anxiety sub-domain of the Piers-Harris 2 served as a measure of temperament for the present study. This sub-domain was used as a temperament measure by Holder and Coleman (2008, in press) and was found to significantly correlate with measures of happiness. The sub-domain’s 14 items explore feelings of worry, nervousness, shyness, sadness, and fear, which are essential components to the personality trait neuroticism (Eysenck, 1986). Examples of items from this sub-domain include “I am often sad”; “I am shy”; “I am nervous” and “I worry a lot”. Given that neuroticism is strongly linked to happiness in adults (e.g., Brebner et al., 1995), it is likely that the Freedom from Anxiety sub-domain of the Piers-Harris 2 will be related to happiness in children (i.e., the more free from anxiety students rate themselves, the happier they will be rated). Although the PiersHarris 2 has a sub-domain designed to explore happiness and satisfaction, this sub-domain was not used as a happiness measure for two main reasons. First, this sub-domain was designed to measure happiness and satisfaction, whereas measures that were designed to specifically target happiness were preferred for the study. Second, 4 of the 10 items overlapped with the Freedom from Anxiety sub-domain and using the happiness and satisfaction sub-domain may have artificially increased the relation between these two domains. 2.2.2 Faces Scale. The Faces Scale (see Appendix B) is a single-item measure, depicting seven simple drawings of faces, arranged in a horizontal line, that represent the participant’s overall feeling of happiness (“Overall, how do you usually feel?”). The participants were required to fill in a circle below the face that best represented their feelings ranging from “very unhappy” (depicted by a very down-turned mouth) to “very happy” (depicted by a very up-turned mouth). It is similar to that used by Andrews and Withey

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(1976) with an adult sample (although in this study the order of the faces was reversed), and identical to that used by Holder and Coleman (2008, in press) with children. Single item measures of happiness have been shown to be reliable and valid, in addition to being a viable option in large-scale studies (Abdel-Khalek, 2006). The Faces Scale is significantly correlated to standardized measures of happiness, supporting its validity as a happiness measure (Holder & Coleman, 2008; in press). In addition, previous studies have indicated that the large majority of respondents tend to select one the three happiest faces on the scale (e.g., Holder & Coleman, 2008, in press). Figure 1 replicates these findings and supports the reliability of the Faces Scale. The use of reports by knowledgeable others (e.g., parents rating their children) has been shown to be reliable and valid, particularly regarding measures of personality (Funder, 1991) and happiness or well-being (Lepper, 1998). Furthermore, Holder and Coleman (2008, in press) showed good agreement between children’s self-reports and parent reports of their children on a measure of happiness. 2.2.3 Subjective Happiness Scale (Lyubomirsky & Lepper, 1999) (see Appendix B). This measure (see Appendix B) assesses the participant’s subjective happiness from a global perspective. Participants were asked to respond to four items using a 7-point Likert-type scale (e.g., “Compared to most of my peers, I consider myself:” 1 (less happy) to 7 (more happy)). In studies with adults, this measure shows high internal consistency (Cronbach’s alpha ranged from .79 to .94) and good test-retest reliability (e.g., after one month, r = .90) (Lyubomirsky & Lepper, 1999). It is a reliable (α = .85) (Tkach & Lyubomirsky, 2006) measure of happiness, and shows convergent and discriminant validity (Lyubomirsky & Lepper, 1999). In order to adapt the questions to a Grade 4 reading level for use with children, the statements in Questions 3 and 4 that read, “To what extent does this

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characterization describe you?” were changed to, “How much does this sentence describe you?” All other wording was retained verbatim. Reliability analyses of the current sample indicate that this measure may not be as reliable with children (α = .67), but that it could likely be improved with modification of an item (see Appendix C). 2.2.4 Oxford Happiness Questionnaire, Short Form (Oxford Happiness Questionnaire) (Hills & Arygle, 2002) (see Appendix B). This measure uses eight items to assess the participant’s personal happiness. Participants were asked to respond to the items using a 6-point scale anchored with “strongly disagree” and “strongly agree.” The statements express how participants may feel about themselves (e.g., “I feel that life is very rewarding”). Research has confirmed that in studies with adults, the Oxford Happiness Questionnaire Short Form shows good internal consistency (e.g., α = .62) as well as short-term test-retest reliability (e.g., r = .69 after two weeks) (Cruise, Lewis, & McGuckin, 2006). Reliability analyses of the current sample suggest that this measure may be less reliable with children (α = .58) (see Appendix C). 2.2.5 Emotionality Activity and Sociability Temperament Survey (EAS) (Buss & Plomin, 1984). This measure (see Appendix B) consists of 20 items using a 5-point scale ranging from 1(not very typical/characteristic) to 5 (very typical/characteristic). There are five statements for each of the four domains: Emotionality (e.g., “tends to be somewhat emotional”), Activity (e.g., “is always on the go”), Sociability (e.g., “prefers playing with others rather than alone”), and Shyness (e.g., “tends to be shy”). The EAS was chosen from a multitude of temperament measures because it is short and straightforward, has forms for multiple informants, is not affected by gender or age of the child being rated (Boer & Westenberg, 1994), and has been used extensively with clinical and community samples

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(Masi et al., 2003). Validity and reliability of parent reports are consistently found to be good (Masi et al.); however in their psychometric testing, Buss and Plomin (1984) found test-retest reliability correlations to be stronger for emotionality (e.g., .72) and activity (e.g., .80) than for sociability/shyness (e.g., .58). Thus, it is important to conduct confirmatory factor analyses when using the EAS to determine the stability of the factors (see Results). Reliability analyses revealed reliability to be stronger for parents’ ratings than for children’s ratings (see Appendix C) Although originally developed for completion by parents, our study also sought to determine whether the EAS could be reliably used as a self-report measure for children in Grades 4-6. As such, children also completed the EAS as a self-report measure of temperament. For the children’s self-report the wording of the items was changed to reflect personal pronouns (e.g., “I”) instead of the more general language used on the parent report (e.g., “Child”). 2.3 Procedures Permission to conduct the present study was obtained first from the Administration of both School District #23 (SD23) and of the Independent School Council, followed by permission from individual school principals (see Appendix A). Once a principal agreed, teachers at his or her school were asked for their classroom’s participation (see Appendix A). Children from participating classrooms were given consent forms and information letters (see Appendix A) to take home to their parents. Only children whose parents agreed to their participation were surveyed. In each classroom, before the start of the survey, participating students were asked for their informed assent (see Appendix A), which they indicated by circling “yes” or “no” on their sheet after being read the instructions. Teachers were also

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asked to participate by rating how happy they felt each participating student was. Participating students, parents, and teachers were free to withdraw at any time without penalty. The questionnaires were administered in a quiet setting within the school (e.g., classroom, library) and averaged 30-35 minutes to complete, with all students completing their surveys within 20-40 minutes. One or two researchers were available to answer individual students’ questions throughout the session. Participating students were given a brief, standardized explanation of the purpose of the study (i.e., to learn more about what contributes to children’s happiness) as well as how to answer the different types of questions (i.e., Likert-type ranges versus yes-or-no questions). They were instructed to read each question carefully, and to choose the response option that was most appropriate for them. Students not participating in the survey completed a quiet, teacher-approved individual activity at their desks. Upon completion, teachers and children were given the opportunity to ask questions. They were then thanked for their participation in the study and informed that a summary of the findings would be presented in a letter to be sent home with each student in participating classrooms (whether they participated in the study or not), upon completion of the study. Only group results were evaluated and no individual results were available to participants. 2.4 Data Analyses Ratings of children’s happiness [i.e., Children’s self-ratings of happiness using the Faces Scale (children’s Faces Scale), parent ratings of their child’s happiness (parents’ Faces Scale), ratings from the Subjective Happiness Scale, and ratings from the Oxford Happiness

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Questionnaire)] were used as criterion variables. Temperament measures (Emotionality, Activity, Sociability, Shyness, and Freedom from Anxiety) were used as predictor variables. Data Analyses were completed in several phases. Variables of interest were examined to ensure they were adequately distributed and met the statistical assumptions for the appropriate analyses. In addition, descriptive statistics and Pearson Product moment correlations were calculated to gain an overall perspective of the data. Following initial analyses, confirmatory factor analyses (CFA) were conducted on both the parent and child ratings of the EAS temperament survey to determine whether the data fit the original model proposed by Buss and Plomin (1984). CFA uses structural equation modeling to determine how well the data set fits a proposed model. It tests the hypothesis that a relationship exists between the observed variables and their underlying latent constructs (Tabachnick & Fidell, 2001). In order to determine how well the proposed model describes the current dataset, one must examine the fit statistics found in the output of a CFA. According to Tabachnick and Fidell, the χ2 statistic is often unreliable in large sample sizes; thus, other fit indices are used. The Comparative Fit Index (CFI) and Root Mean Square Error of Approximation (RMSEA) are the most frequently reported fit indices; a CFI of .90 or greater indicates an acceptable fit, as does an RMSEA of approximately .06 or less (a RMSEA of .10 or greater indicates a poor fit). The Normed Fit Index (NFI) is another indication of fit, with values greater than .95 indicating a good fit. It is unwise to depend solely on one measure of fit; therefore, considering a group of indices together will give the researcher a more accurate picture of the data. Following the CFAs, regression analyses were performed to investigate how well temperament variables predicted happiness in children.

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2.5 Data Cleaning In total, data were collected from 320 students and their parents. Of these, 9 cases were incomplete: in 5 cases there was no information provided by the parents, and in 4 cases, students completing the surveys had disabilities (e.g., autism) and did not have sufficient time/interest/attention to finish the survey. Since cases containing sufficient information from both parents and students were essential to these analyses, these 9 cases were deleted, resulting in a sample of 311 students and their parents. In each variable of interest, missing cases were not systematically distributed and consisted of less than 3% of the sample. Since missing cases were scattered throughout the dataset, deleting these cases would have substantially reduced the sample size. As such, these values were replaced with the appropriate group mean. Although this can be a conservative measure, there is no a priori knowledge to suggest an appropriate value for any of the relevant variables, and when missing values are scattered as they are in the present study, inserting the mean is just as effective as estimating the value through regression (Tabachnick & Fidell, 2001). Multivariate outliers were identified and selected out of further analyses. Depending on the combination of variables being analyzed, this left between 301 and 311 cases. Results of tests for linearity, homoscedasticity, and multicollinearity were satisfactory and did not indicate the need for correctional action. Skewness analyses were conducted to determine the normality of all variables of interest. The distributions for the following variables violated the assumptions of normality and so appropriate transformations were performed to bring these variables into an acceptable range: children’s self-ratings of Emotionality, Shyness, Sociability, and the children’s Faces Scale, parents’ Faces Scale, and the Oxford Happiness Questionnaire, Short

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Form. Table 1 shows the type of transformation performed in addition to the skewness and kurtosis values for these variables before and after the transformation. The transformations generally improved the variables. All reported analyses used these transformed scores. Table 2 lists the variables used in the final analysis, including the means and standard deviations for each variable. While the parents’ and children’s Faces Scales are single item measures, all of the other items are composites. For both the parents’ and children’s EAS Temperament Survey, each child’s score for the four domains is an average of the five items that comprise the domain. For example, a child’s score on the Emotionality domain would be an average of the scores of the five items that explore emotionality. In addition, each child’s score on the Subjective Happiness Scale is an average of its four items, while the score on the Oxford Happiness Questionnaire, Short Form is an average of its eight items. Finally, each child’s score on the Freedom from Anxiety Sub-domain is an average of the 14 yes/no items (given a score of 0 or 1) that comprise it.

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Table 1 Skewness and Kurtosis of Study Variables Before and After Transformation Skewness (SE) Transformation

No N = 311 Note. For all happiness variables, higher numbers indicate that the respondent is more happy. For the parent and child EAS temperament variables, higher numbers indicate the item is more characteristic of the child (e.g., higher numbers on the Activity domain would indicate the child is more active). For the Freedom from Anxiety Sub-domain, higher numbers indicate a child is more free from anxiety.

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Figure 1. Participants’ Ratings of Happiness Using the Faces Scale Overall, how do you usually feel?